Implementation of different relationship estimate methodologies in breeding value prediction in kiwiberry (Actinidia arguta)

Abstract

In dioecious crops such as Actinidia arguta (kiwiberries), some of the main challenges when breeding for fruit characteristics are the selection of potential male parents and the long juvenile period. Currently, breeding values of male parents are estimated through progeny tests, which makes the breeding of new kiwiberry cultivars time-consuming and costly. The application of best linear unbiased prediction (BLUP) would allow direct estimation of sex-related traits and speed up kiwiberry breeding. In this study, we used a linear mixed model approach to estimate narrow sense heritability for one vine-related trait and five fruit-related traits for two incomplete factorial crossing designs. We obtained BLUPs for all genotypes, taking into consideration whether the relationship was pedigree-based or marker-based. Owing to the high cost of genome sequencing, it is important to understand the effects of different sources of relationship matrices on estimating breeding values across a breeding population. Because of the increasing implementation of genomic selection in crop breeding, we compared the effects of incorporating different sources of information in building relationship matrices and ploidy levels on the accuracy of BLUPs’ heritability and predictive ability. As kiwiberries are autotetraploids, multivalent chromosome formation and occasionally double reduction can occur during meiosis, and this can affect the accuracy of prediction. This study innovates the breeding programme of autotetraploid kiwiberries. We demonstrate that the accuracy of BLUPs of male siblings, without phenotypic observations, strongly improved when a tetraploid marker-based relationship matrix was used rather than parental BLUPs and female siblings with phenotypic observations.

Molecular breeding of flower load related traits in dioecious autotetraploid Actinidia arguta

“…Studies on genomic selection in A. arguta , including fruit load, also showed a moderate heritability. Combining this finding with a study on the inheritance of fruit load in A. chinensis suggests a robust heritability estimation of flower load traits in our study, considering only one year of observations (Cheng et al 2004 ; Mertten et al 2023 ). This assumption is based on a strong correlation between flower load and fruit load.…”

“…Additionally, male progeny are selected for yield based on their family mean, as they do not provide phenotypic information on yield and require further progeny testing, which is costly and time-consuming. Utilizing marker-based relationship information reduces the breeding cycle by eliminating the need for additional progeny testing of selected males genotypes (Mertten et al 2023 ). Our study is a powerful tool; when both sexes and a marker-based relationship matrix are considered, it will enhance the effectiveness of superior selection and expedite the breeding program for dioecious crops like A. arguta .…”

“…The population consisted of an NC II of 13 female parents crossed with 2 male parents, resulting in 26 families, and a second NC II of 2 female parents crossed with 13 male parents, resulting in 22 families. The female parents of the first NC II and male parents of the second NC II were selected from a prior factorial design (Supplementary Table 1 ) (Mertten et al 2023 ). The trial was established for four years before flowering vines were assessed and the final number of seedlings per cross ranged from a minimum of 2 seedlings to a maximum of 80 seedlings.…”

“…ANGSD was used for SNP calling with region selection based on target intervals (Korneliussen et al 2014 ). Dosage estimation of tetraploid A. arguta × A. arguta population and SNP filtering were performed using the R-package "Updog" V2, considering allele bias (0.5 < bias < 2), over-dispersion (od < 0.02), and sequencing error (seq < 0.01) (R Core Team 2020 ; Tahir et al 2020 ; Mertten et al 2023 ). Dosage genotypes were called using an empirical Bayesian approach, assuming tetraploid (4 x ) as 0 (AAAA), 1 (AAAB), 2 (AABB), 3 (ABBB), and 4 (BBBB) (Gerard et al 2018 ).…”